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<p>Aptamers, as single-stranded DNA (ssDNA) or RNA oligonucleotides, are pivotal in biosensing due to their high affinity. However, excessive lengths of these nucleic acid probes can impair their binding affinity and target recognition efficiency. Traditional optimization methods, such as static structural modeling, fail to capture the dynamic interactions between aptamers and biological macromolecules. Therefore, optimizing aptamer length to enhance affinity while maintaining effective target recognition is crucial. Here, we employed 600ns molecular dynamics (MD) simulations using the amberff14sb and parmbsc1 force fields, alongside molecular mechanics/generalized Born surface area (MM/GBSA) free energy calculations to optimize the binding affinity of a ssDNA aptamer targeting the hemagglutinin-neuraminidase (HN) protein—a critical surface receptor of Newcastle disease virus (NDV) responsible for viral attachment and entry. By systematically truncating the aptamer sequence guided by normalized criteria to eliminate length bias, we identified a 10-nucleotide variant (fqh-2) that exhibited a hydrogen bond efficiency ratio (HBER) of 1.055 and a binding free energy efficiency ratio (BFEER) of -5.124&#xa0;kcal/mol, reflecting enhanced interactions with the HN protein. Furthermore, a graphene oxide (GO)-based fluorescence quenching assay confirmed a threefold increase in binding affinity for the optimized aptamer, aligning with computational predictions. This study not only provides a dynamic structure-guided framework for aptamer optimization but also lays a theoretical foundation for further advancements in optimizing and tailoring aptamers for specific applications.</p>

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Improving aptamer binding affinity for HN protein of newcastle disease virus: molecular dynamics simulations and MM/GBSA calculations studies

  • 期刊论文

  • 发表日期：

    2026年5月3日

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  • Shuang Jiang,
  • Xu Wen,
  • Xiaoling Zheng,
  • Xue Wang,
  • Xianlu Lei,
  • Yong Xie,
  • Tao Le

摘要

Aptamers, as single-stranded DNA (ssDNA) or RNA oligonucleotides, are pivotal in biosensing due to their high affinity. However, excessive lengths of these nucleic acid probes can impair their binding affinity and target recognition efficiency. Traditional optimization methods, such as static structural modeling, fail to capture the dynamic interactions between aptamers and biological macromolecules. Therefore, optimizing aptamer length to enhance affinity while maintaining effective target recognition is crucial. Here, we employed 600ns molecular dynamics (MD) simulations using the amberff14sb and parmbsc1 force fields, alongside molecular mechanics/generalized Born surface area (MM/GBSA) free energy calculations to optimize the binding affinity of a ssDNA aptamer targeting the hemagglutinin-neuraminidase (HN) protein—a critical surface receptor of Newcastle disease virus (NDV) responsible for viral attachment and entry. By systematically truncating the aptamer sequence guided by normalized criteria to eliminate length bias, we identified a 10-nucleotide variant (fqh-2) that exhibited a hydrogen bond efficiency ratio (HBER) of 1.055 and a binding free energy efficiency ratio (BFEER) of -5.124 kcal/mol, reflecting enhanced interactions with the HN protein. Furthermore, a graphene oxide (GO)-based fluorescence quenching assay confirmed a threefold increase in binding affinity for the optimized aptamer, aligning with computational predictions. This study not only provides a dynamic structure-guided framework for aptamer optimization but also lays a theoretical foundation for further advancements in optimizing and tailoring aptamers for specific applications.